より多くの、異なるデータの影響とは

When it comes to detecting fraud, Insurers know that better data means better fraud decisions. Many insurers have relied on first-party data collected from its own policyholders and employees. The advent of the digital age, however, means that there is far more data than insurers can easily collect themselves. 

Sources such as social media data, satellite data, financial data, and public records can remove blind spots and provide more signals to fraudulent activities. By contrast, if insurers can’t access or analyze these data sets effectively, these blind spots turn into increased costs and bad policyholder experiences.

How does external data benefit insurers?
With the addition of external data, insurers can make improved decisions about insurance fraud. They can find fraud faster and more accurately while implementing automated decisions and workflows. Insurers can enhance existing fraud detection, or discover entirely new fraud methods and networks. They can also significantly reduce the time spent researching false positives and in turn, dedicate more time to investigating actual fraud.

So, what are some examples of the benefits that external data sets provide?

• Specialist data providers – Leading data providers, such as the National Insurance Crime Bureau (NICB), LexisNexis, and Legentic, provide a comprehensive view of criminal and property history that can augment public records. Provider data is pre-vetted and aggregated, and can be applied to a particular line of business or product through one single entry point via the Shift Claims Fraud Detection product.
• Satellite – Satellite imagery data of roofs and other structures is utilized in evaluating property claims and underwriting. For example, insurers can access satellite images to see whether a policyholder’s roof has truly been damaged following a large storm.
• Business/government/provider records – Links and integrations (potentially utilizing natural language processing to extract data points) is leveraged to increase accuracy on provider/patient scoring, government regulation, or policy data. This information is often used to uncover undisclosed risks, such as unlisted second drivers or unmentioned criminal records, that might affect premiums during underwriting.
• Social – Data from social media platforms including Facebook, Instagram, Twitter and Strava has been useful in corroborating (or contesting) claims. For example, the claimant is pictured on social media doing something, such as strenuous physical activity, when their claim states they are physically unable to do so.

Gathering external data is good, but utilization makes the difference
While gathering external data sets is a starting point, utilizing that data makes the difference when stopping more fraud. With Shift’s approach, insurers don’t have to pick and choose from available external data sets. Instead, Shift data scientists and data partner experts pre-integrate the most relevant external data into Shift Claims Fraud Detection. This results in a large custom portfolio of highly valuable information for insurers. 

Additionally, Shift continuously reviews, integrates, and updates external data, providing our customers with more than 100 valuable and validated sources across the globe. This service is bundled into our claims fraud detection solution, and is designed to take the headache out of managing external data.

A great example of this managed external data approach comes from a common fraud scenario: Detecting when a homeowner may decide to claim pre-existing roof damage as the result of a storm. (We see this in almost every region where we operate.) These false claims are significant because they force insurers to pay for repairs that cost $7,000 USD on average.

With Shift’s managed external data approach, our AI solution automatically flags false roof damage claims with two pre-integrated data sets. First, Shift’s software can query local meteorological records to confirm that the storm actually happened. Second, the Shift software can bring up before-and-after satellite photos of the policyholder’s house. Shift can use its built-in image recognition capabilities to confirm that the building’s roof was damaged before the storm occurred. This leaves a simple case for investigators to follow.

Lastly, insurers may have their own unique data, which Shift can integrate into our already comprehensive datasets. That way, insurers leverage an ecosystem of internal and external data sources that best suits their needs. Using this tailored intelligence asset, insurers can detect more fraud while streamlining the claims process for their policyholders, recovering costs while delivering positive experiences.

By incorporating external data, insurers can continue to move confidently towards improved decision making. For more information, request a demo today.